Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - PROPHESY (Platform for rapid deployment of self-configuring and optimized predictive maintenance services)

Teaser

Predictive maintenance (PdM) technologies continually monitor machines and equipment in order to identify symptoms of wear and other failures. In this way there is no need to keep excessive inventory through overproduction, as a means of alleviating the effects of break-downs...

Summary

Predictive maintenance (PdM) technologies continually monitor machines and equipment in order to identify symptoms of wear and other failures. In this way there is no need to keep excessive inventory through overproduction, as a means of alleviating the effects of break-downs, and the manufacturers can proactively undertake repairs and replacements, prior to experiencing more expensive problems. However, despite these proclaimed benefits of predictive maintenance, the majority of manufacturers have not fully implemented PdM in their FMECA (Failure Mode, Effect and Criticality Analysis) operations and, instead, apply less efficient approaches such as condition-based or preventive maintenance.
PROPHESY project targets is to provide, validate and develop a viable route to market for a novel PdM platform, which will enable end-to-end development, deployment and operationalization of adaptive self-configurable PdM services, based on the combination of leading-edge CPS components (i.e. CPS architectures, data analytics algorithms for PdM, augmented reality) and novel business models. PROPHESY will enable the development of PdM services considering both the technical excellence and the business relevance of the solution, towards optimizing technical characteristics (e.g., latency, scalability, response time, adaptivity level) and business parameters (e.g., OEE (Overall Equipment Effectiveness), product quality, delivery times, inventory costs) at the same time. Likewise, PROPHESY will also facilitate the deployment of new maintenance concepts, such as the expanded use of remote support and AR as part of predictive maintenance solutions.
The main elements of the PROPHESY solution are the following:
PROPHESY-CPS: A CPS platform tailored to and optimized for predictive maintenance, with features associated with automatic data collection, data sources interoperability, data analytics and maintenance-driven production processes.
PROPHESY-ML: Predictive Data Analytics Toolbox for Self-Configuring and Self-Adaptive PdM.
Remote Visualization & PROPHESY-AR: Development and Integration of Visualization and Augmented Reality Services for Remotely Supported maintenance.
PROPHESY-SOE: Specify and implement methodologies and tools for the dynamic composition of PdM components into integrated PdM programmes and turn-key solutions.

Work performed

The work performed from the beginning of the project is in line with the work-plan of the Description of Action. The PROPHESY platform specifications and architecture were prepared. Also, the identified digital models and interoperability techniques serve as the basis for semantic interoperability of diverse data sources across production lines and factories. The first prototype for data collection was prepared, along with a report for the models of the machines and tools that will be supported by the machine learning toolkit (PROPHESY-ML). The first PROPHESY-CPS integrated system was developed within the first reporting period.
There was also progress in the dashboards to be used on different production levels and on the definition of the augmented reality (AR) functionalities of the platform. The initial versions of the dashboards were integrated into the PROPHESY-CPS system tailored to the use cases of the first demonstration in the two pilot sites at Jaguar Land Rover (JLR) in Wolverhampton, UK and at Philips (PHI) in Drachten, Netherlands, NL.
For the pilot validation through demonstrators in the two pilot sites (PHILIPS and JLR), the specifications for the type and structure of data that will be used, the means of their availability, the technical and non-technical aspects of the pilot sides, were identified and reported. The first implementation and testing of the PROPHESY-CPS platform for the two pilot cases and the initial demonstration of the system was performed as planned within the first reporting period and the outcomes are reported in the relevant deliverables.
The initial work on the exploitation includes the exploitation and sustainability activities, the individual exploitation plans of the partners and the plans for the joint exploitation and longer-term viability of the project’s ecosystem & market platform.
An important dissemination activity was the organization of the first PROPHESY workshop on Predictive Maintenance at PHILIPS premises in Drachten, Netherlands on January 2019. The main objective of this workshop was to present the initial results of PROPHESY project to a community of relevant stakeholders and to bring together several EU manufacturing and Predictive Maintenance (PdM) related projects, to assist in the exchange of knowledge, best practices and ideas, and promote inter-project collaboration.

Final results

The PROPHESY system and its underlying components will provide the means for manufacturers, machine vendors and PdM solution providers to innovate in predictive maintanence services and processes. Based on the algorithms of the PROPHESY-ML toolbox, manufacturers and machine vendors will be able to derive predictive insights and continually monitor the degradation patterns of the various assets, while at the same time anticipating failures. PROPHESY-CPS will provide support for closed loop manufacturing processes, which will be driven by predictions about the status and anticipated operating life of components. Using PROPHESY-SOE manufactures and machine vendors will be able to assemble solutions that schedule maintenance in a way that reduces failure rates. PROPHESY-AR will additionally shorten the time needed for actually performing the repair (e.g., based on faster remote support by the machine vendor if needed). PROPHESY-AR is therefore a key differentiating factor of PROPHESY solutions, when compared to state-of-the-art PdM platforms.
The two complex demonstrators of the project will provide tangible and realistic showcases on the benefits of using PdM in general and PROPHESY-PdM in particular, including benefits associated with increased OEE, extended life of components, reduction of unplanned downtimes and more.
Based on the produced predictions of manufacturing problems, PROPHESY will also mitigate the possibility of accidents that could be caused as a matter of unanticipated machine failures or poor maintenance.
In the end, PROPHESY-PdM will have a positive impact on manufacturers by enabling them to leverage the benefits of predictive maintenance:
- Higher OEE and reduced equipment costs, as PROPHESY-PdM will facilitate repairs prior to failure, which will lead to reduced costs for components and reduction in the labor needed for the repair process.
- Optimized labor costs, as the effort of replacing specific components instead of the entire equipment is much less. Furthermore, PROPHESY-PdM will result in a smaller frequency of repairs for critical equipment (i.e. reduced “critical callouts”).
- Increased productivity for employees and the overall production processes. On the one hand employees will be offered insights that would enable them to replace the right component at the right time, while on the other production will be overall disrupted for a shorter time when compated to unscheduled or poorly scheduled maintenance. Hence, the planned downtime will be reduced, while employees’ time and effort will be better exploited.
- Increased safety, as the earlier fixing of potential problems can enable employees to work under safer conditions.

Website & more info

More info: http://prophesy.eu/.